1. Field of the Invention
The present invention generally relates to thoracic radiology, and more particularly to techniques for thoracic radiology that account for respiratory motion during four-dimensional computed tomography (4D CT).
2. Background Description
Respiratory motion creates several problems for thoracic radiology. It degrades anatomic position reproducibility during imaging. It necessitates larger margins during radiotherapy planning. And it causes errors during radiation delivery. Clinically significant lung tumor motion cannot be predicted by any known clinical parameters, suggesting that tumor motion must be explicitly determined for each patient. In fact, recent European Organization for Research and Treatment of Cancer (EORTC) guidelines state that “An assessment of 3D tumor mobility is essential for treatment planning and delivery in lung cancer.”
Existing methods to account for respiratory motion during CT imaging include breath-hold, respiratory gating, and 4D CT. Four-dimensional thoracic CT images that account for respiratory motion have successfully been acquired using single-slice scanners, however, the authors of these works acknowledge the temporal and spatial limitations of 4D acquisition with current single-slice technology. Multi-slice 4D CT scans have been acquired using an axial/cine method at Washington University, Memorial Sloan Kettering Cancer Center, and Massachusetts General Hospital and by using a helical method at the MD Anderson Cancer Center. Four-dimensional cone-beam CT scans have been acquired using a benchtop system by Taguchi as well as clinically at the Netherlands Cancer Institute. Four-dimensional CT scans can be used to determine tumor motion and tumor-motion-encompassing treatment volumes—in the absence of respiratory management devices—as well as to employ the data for 4D planning and delivery. Individual phases of the 4D CT scan can be used for respiratory gated radiotherapy planning.
The use of 4D thoracic CT has been developed for and applied to radiation oncology patients. However, high-quality 4D CT data, along with accurate deformable image-registration algorithms to automate analysis of this data, could play an important role in the analysis of lung function for a variety of pulmonary diseases. The changes in local density of the lung as a function of respiration could be automatically detected and the abnormal regions displayed, leading to faster diagnosis.
Current 4D thoracic CT techniques build on those existing for cardiac imaging, in which the cardiac signal is input to the CT scanner during the sinogram evolution, from which image reconstruction at several cardiac phases can occur. However, although successive cardiac cycles are relatively reproducible under non-stressed conditions, a factor limiting the success of 4D thoracic CT is the irregularity of respiratory cycles in both displacement and cycle-to-cycle periods. Irregularity manifests itself as imaging artifacts, leading to anatomical mismatches, or there is insufficient acquisition of projection data to reconstruct a full image.
To reduce this irregularity, audio and audiovisual breathing-training methods have been applied to try to improve the quality of 4D thoracic CT data. However, even with audiovisual breathing training, respiration irregularities remain as shown in FIG. 1. FIG. 1 shows coronal images from a 4D CT scan at three respiratory phases for a patient undergoing breathing training. While the left image 101 in FIG. 1 is artifact free, there is an artifact 110 near the dome of the right diaphragm 120 in the center 102 and right 103 images. Thus, whilst taking a similar approach to 4D cardiac CT methods is a good first approximation, further development is necessary to improve 4D CT acquisition.
Four-dimensional computed tomography (4D CT) acquisition methods that explicitly account for respiratory motion have been developed recently in academic and commercial settings. 4D CT is generally acquired either by sinogram or image sorting based on a post-acquisition procedure using external respiration signals. The patient's ability to maintain reproducible respiratory signals is the limiting factor during 4D CT. Methods of breathing coaching, e.g., audiovisual biofeedback, can improve respiration reproducibility, however, significant variations remain and cause artifacts in the 4D CT scan.